We evaluated empirically the performance of various methods of calculating age-adjusted survival estimates when age-specific data are sparse. We have illustrated that a recently proposed alternative method of age adjustment involving the use of balanced age groups or age truncation may be useful for enhancing calculability and reliability of adjusted survival estimates. Age adjustment is widely used in studies comparing survival of different cancer patient populations. Most commonly, the comparison is made by calculating a weighted average of agespecific survival estimates, using weights reflecting the age distribution of some defined standard population. There has, however, been a large diversity in the practice of age adjustment, mainly concerning the definition, the number and width of the age groups, and methods to overcome difficulties when the agespecific survival could not be calculated. Such situations are not uncommon in comparative survival studies, particularly when data for rare cancers or data from registries covering smaller populations is involved. Examples of the practice of age adjustment of cancer survival are given in Table 1.Recently, an alternative method was proposed for age adjustment of survival estimates , in which weights are assigned to the patients before one carries out the survival analysis. Weights are determined as the percentage of patients in the age group the patient belongs to in the standard population divided by the corresponding percentage in the study population. Survival analysis is carried out using the weighted individual data, without the need to calculate age-specific survival estimates .In this paper, we empirically evaluate and compare the performance of different options of age adjustment methods in situations when age-specific data are sparse.
MATERIALS AND METHODS
Data setData from the Zimbabwe National Cancer Registry (ZNCR) (Chokunonga et al, 2000;Parkin et al, 2003) were used. The registry, established in 1985, covers the population of the Zimbabwean capital, Harare. In terms of operational circumstances, which have been described in detail elsewhere, the registry may be considered as a typical example for an urban developing country cancer registry with appropriate data quality outcomes (Sankaranarayanan et al, 1998;Parkin et al, 2003;Chokunonga et al, 2004). Survival results for a large number of cancer sites were recently published elsewhere (Gondos et al, 2004).We assessed various options of age adjustment of 5-year survival estimates among patients diagnosed with five different types of cancers in 1993 -1997 and followed up until 31 December 1999: skin melanomas, breast, cervical and prostate cancer and lymphomas. Breast and cervical cancers were included because they were represented by relatively large samples. Prostate cancer, for which only 3-year survival could be calculated due to the lack of patients with a 5-year follow-up time, was included because of the unusual age distribution (high proportions of older patients). Lymphomas were included becau...